Adhydro: QUASI-3D HIGH PERFORMANCE HYDROLOGICAL MODEL Fred L. Ogden, Professor, [email protected]; Wencong Lai, Post-Doctoral Asso
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ADHydro: QUASI-3D HIGH PERFORMANCE HYDROLOGICAL MODEL Fred L. Ogden, Professor, [email protected]; Wencong Lai, Post-doctoral Associate, [email protected]; Robert C. Steinke, Research Scientist, [email protected] Abstract: In recent decades, computational models have been developed to solve point-scale process models using physics-based or conceptual approaches. The integration of these processes across space-time has been limited by computational power to either high-resolution over small spatial domains, or coarse resolution over large spatial domains. These modeling approaches have lead to improved understanding at both small and large scales, but have required parameterization of important phenomenon, and the corresponding lack of model sensitivity to changes and uncertainties in parameter values. The CI-WATER project, a cooperative agreement between the US National Science Foundation EPSCoR program and the Utah and Wyoming Ph.D.-granting universities, is developing tools to cross the digital divide that impedes application of high performance computing (HPC) to solve hydrological science, engineering, and management problems. We are developing software tools to ease simulations using HPC resources. These tools include web-aware model setup and visualization tools that will interact with dedicated HPC systems or cloud systems, workflows for model setup, and web services for data provisioning. These tools are being developed with generality in mind, supporting a range of HPC-aware models, including the US Army Corps of Engineers Gridded Surface/Subsurface Analysis (GSSHA) model, and an unstructured mesh high-resolution physics-based hydrological model, called ADHydro. The ultimate objective of ADHydro development is perform multi- decadal simulations of large watersheds such as the Upper Colorado River above Lake Powell (288,000 km2) in the contexts of land use, water use, and climate changes. We are cooperating with the US Army Corps of Engineers, Engineering Research and Development Center, Coastal and Hydraulics Laboratory, and the National Center for Atmospheric Research, Research Applications Laboratory in linking with their HPC hydrological and atmospheric models. This presentation will showcase our software tools under development. INTRODUCTION Physically-based, spatially distributed hydrologic models have been widely used in hydrologic modeling and watershed management, such as SWAT (Arnold et al., 1993), MIKE SHE (Refsgaard and Storm, 1995), and GSSHA (Downer and Ogden, 2004). Applications of such hydrologic models for large watersheds typically use coarse spatial and temporal resolution. Detailed simulation of larger watersheds with hyperresolution hydrological prediction is a grand challenge because significant computational resources and data are required (Wood et al., 2011). In recent years, a growing number of distributed hydrological models have been developed in parallel computing environments with the advent of high performance computing (Apostolopoulos and Georgakakos, 1997; Cui et al., 2005; Wang et al., 2011; Vivoni et al., 2011; Hwang et al., 2014). HPC hydrological models coupled with meteorological models are capable to model high-resolution long term simulation in large watersheds in order to evaluate the impact of climate and land use changes. HPC hydrological models can be classified into two categories according to their parallel algorithm. One category of such models, for example ParFlow(Ashby and algout, 1996; Kollet and Maxwell, 2006), PFLOTRAN (Mills et al., 2007), PHGS (Hwang et al., 2014), utilize pre-developed HPC packages or libraries for parallel preconditioner and solver. The other category of models adopt spatial domain decomposition with either sub-basin based (Li et al, 2011; Vivoni et al., 201; Wu et al., 2013) or unit based message passing (Cheng et al., 2005; Liu et al., 2014). Parallelization of hydrologic models can be implemented using parallel programming standards such as Open Multi-Processing (OpenMP), Message Passing Interface (MPI), grid computing, and other parallel programming toolkit. The PHGS (Hwang et al., 2007) applied OpenMP in the HydroGeoSphere model using parallel matrix solver. The FSDHM model was parallelized using OpenMP by dividing simulation units into hydrologic independent layers (Liu et al., 2014). However, OpenMP only works in shared memory machines. Yalew et al. (2013) parallelized the SWAT watershed model using the distributed grid computing by splitting large scale model into small scale components. As MPI can distribute computing loads and converge results through message transfer and communication between processors, it is the most used technology in parallel hydrologic models for domain decomposition (Li et al, 2011; Vivoni et al., 2011; Wang et al., 2011; Wu et al., 2013). However, using the MPI library for data partitioning and communication is not straightforward. The pWASH123D model (Cheng et al., 2005) utilizes the DBuilder (Hunter and Cheng, 2005) parallel data management toolkit, which hides the MPI scheme for map generating, sending, and receiving between meshes with simple Application Programming Interfaces (API) and embedded ParMETIS partitioner library (Karypis et al., 1997). The development of the ADHydro model is presented here. The ADHydro model is a high- resolution physics-based distributed hydrological model developed in parallel computing environment. The merits of the model comparing with other HPC hydrologic models include: an innovative method for modeling vadose zone dynamics, a water management module considering reservoirs, diversions and irrigation, a coupled strategy to estimate interception evaporation, and snow processes through the community Noah land surface model with mutiparameterization options (Noah-MP) and the capability to ingest downscaled atmospheric forcing from the Weather Research and Forecasting (WRF) meteorologic model using the CHARM++ parallel programming environment. GEOSPATIAL DATA AND ATMOSPSHERIC FORCING The Upper Colorado River Basin above Lake Powell has a watershed area of approximately 288,000 km2, and total length of streams of 467,000 km. It's located in one of the 21 major geographic regions defined by the USGS hydrologic unit code (Seaber et al., 1987) in the US. In the pre-processing step, topographic base map data were acquired from National Elevation Dataset (NED) 1/3 arc-second Digital Elevation Models (DEMs), and USGS National Hydrography Dataset (NHD) (http://viewer.nationalmap.gov/viewer/). Land cover and land use data were obtained through the 30-meter resolution, 16-class land cover classification National Land Cover Database 2011 (NLCD 2011) (http://www.mrlc.gov/). Soil texture types were aggregated from the NRCS county level Soil Survey Geographic Database (SSURGO) and state- wide State Soil Geographic Database (STATSGO) (http://www.nrcs.usda.gov/wps/portal/nrcs/main/soils/survey/geo/). The TauDEM tools (http://hydrology.usu.edu/taudem/taudem5/) were used to extract channel network from NED DEMs. The resulting channel network and NHD were analyzed and processed by ArcGIS to produce shapefiles and steam network connectivity that includes lakes and reservoirs. The shapefiles were used to generate high resolution unstructured 2D triangular mesh using Triangle (http://www.cs.cmu.edu/~quake/triangle.html). A 1D channel network model with mesh size of 100 meters was also generated. River hydraulic geometry were described in the form of power functions of discharge, which scales with drainage area. Atmospheric forcing for different scenarios was generated using the Weather Research and Forecasting meteorologic model (Michalakes et al., 2004). The WRF model is a mesoscale numerical weather prediction system design to both atmospheric research and operational forecasting needs. Simulation results from WRF, including precipitation, air temperature, air pressure, wind speed, short and long wave radiation and vapor pressure, were used as atmospheric forcing input for ADHydro. The 4 km resolution WRF outputs were downscaled to the high-resolution meshes. ADHYDRO QUASI 3-D DISTRIBUTED HYDROLOGIC MODEL The ADHydro is a high-resolution multi-physics distributed model for hydrological and water resources modeling. Major hydrologic processes are considered, including precipitation and infiltration, snowfall and snowmelt in complex terrain, vegetation and evapotranspiration, soil heat flux and freezing, overland flow, channel flow, groundwater flow and water management. These hydrologic components are described below. The ADHydro model uses the explicit finite volume method to solve conservation laws for overland flow and saturated groundwater flow coupled to river flow. The model has a quasi-3D formulation that couples 2D overland flow and 2D saturated groundwater flow using the 1D Talbot-Ogden finite water-content infiltration and redistribution method (Talbot and Ogden, 2008). This eliminates difficulties in solving the highly nonlinear 3D Richards' equation, while the finite volume Talbot-Ogden infiltration method is computationally efficient, mass conservative, and allows simulation of the effect of shallow groundwater tables on runoff generation. Interception, Evapotranspiration and Snow Melt: Interception, evapotranspiration and snow melt processes are simulated using the Noah-MP model (Niu et al., 2011; Yang et al., 2011). The Noah-MP model considers biophysical processes such as interactive vegetation canopy, multilayer snow pack and soil, overland runoff, and unconfined aquifer for groundwater